CBIRT, Centre of Bioinformatics Research & Tech’s Post

New #AI method, #LINGER, cracks the code on gene regulation! 💡 LINGER, developed by Clemson University scientists, infers gene regulatory networks from single-cell multiomics data by integrating atlas-scale bulk data and prior knowledge. It outperforms existing methods and enables interpreting disease variants from expression data alone. Quick Read: https://lnkd.in/gYViayW2 #bioinformatics #genomics #machinelearning #generegulation #bigdata #sciencenews

Gene&Cell Therapy >> Scientists and startups reveal new gene insertion techniques, though much remains behind closed doors: #ASGCT24: Several secretive and well-funded biotechs are sharing the first glimpses of data from a new suite of gene editing tools that promise to overcome one of the field’s grand challenges: precisely inserting large sequences of DNA, or even whole genes, into the genome. So far, most work with CRISPR gene editing has used the tool to turn off problematic genes. Newer versions of the technology, like base editing and prime editing, can make small changes to one or a few letters of genetic code, respectively. But replacing large swathes of errant code, or uploading brand new ones, has remained a challenge. ReNAgade Therapeutics, SalioGen Therapeutics and Tome Biosciences have been quietly working on new gene insertion techniques. So has David Liu, a prominent gene editing scientist from the Broad Institute of MIT and Harvard. Those startups and Liu all disclosed new technologies this week at the American Society of Gene & Cell Therapy’s conference in Baltimore. Jason Cole “This is our coming-out party, scientifically,” SalioGen CEO Jason Cole told Endpoints News. His company on Tuesday presented data on its experimental therapy for an inherited form of vision loss called Stargardt disease. In a mouse experiment, the approach restored expression of the gene in 40% of photoreceptors and reduced a harmful byproduct believed to contribute to vision loss by a similar amount. Stargardt disease has been tough to tackle with other approaches. The broken gene is too big to squeeze into the viral vectors commonly used in traditional gene therapies. And since the disease can be caused by a large number of different mutations in that gene, fixing those mutations with existing CRISPR tools is impractical. Gene insertion offers a new solution. SalioGen uses a new lipid nanoparticle to deliver a fresh copy of the gene into the eye, which gets stitched into the genome with an enzyme called a transposase, which is familiar to biologists for moving so-called “jumping genes” throughout the genome. SalioGen is working on a similar approach to treat cystic fibrosis in the lungs, which is also caused by several mutations in a large gene. And it hopes that’s just the start. “These integrating technologies can really open up the number of indications we can go after with genetic medicine,” Cole said. A ‘final chapter in genomic medicine’ Gene insertion is the new vanguard of gene editing. The original three biotechs built around CRISPR gene editing — CRISPR Therapeutics, Editas Medicine and Intellia Therapeutics — have all begun early discovery work on gene insertion technologies. And many small startups are developing their own gene insertion tools. Although adding or replacing entire genes isn’t always… #lucidquest #genetherapy #celltherapy

I am proud to share a recent, first author publication from my master's thesis work! I programmed a new method for inferring gene regulatory networks from scRNA-seq data called single-cell temporal inference of gene expression regulation, or scTIGER. It is the first method to infer gene regulatory networks by using the paired dynamics of case versus control data. https://lnkd.in/eDb8sRn6

Profluent is using protein language models to design new gene editing systems. The company has open sourced their first AI-designed gene editor, OpenCRISPR-1, to help accelerate progress in this space. “Attempting to edit human DNA with an AI-designed biological system was a scientific moonshot. our success points to a future where AI precisely designs what is needed to create a range of bespoke cures for disease. To spur innovation and democratization in gene editing, with the goal of pulling this future forward, we are open-sourcing the products of this initiative.”” - Ali Madani, Profluent co-founder and Chief Executive Officer. https://lnkd.in/dVWK_wrE #AIprotein #proteindesign #CRISPR #geneediting #artificialintelligence #biotech

A new method ChIP-DIP maps hundreds of proteins to DNA simultaneously, revealing diverse gene expression regulators in a single experiment! The study marks a major advance in unraveling cell-type specific regulation. Quick Read: https://lnkd.in/gD3R4Epe #bioinformatics #genomics #chipseq #dnasequencing #geneexpression

AI-designed gene editing tools successfully modify human DNA https://buff.ly/3JzfsPZ #geneediting #therapeutics #biotechnology #biotech

📍 Inferring gene regulatory networks from single-cell multiome data using atlas-scale external data Yuan and Duren presented LINGER, a machine-learning method to infer gene regulatory networks from single-cell paired gene expression and chromatin accessibility data.   Key points 📌 A fourfold to sevenfold relative increase in accuracy over existing methods 📌  Incorporating atlas-scale external bulk data across diverse cellular contexts and prior knowledge of transcription factor motifs as a manifold regularization 📌 Revealing a complex regulatory landscape of genome-wide association studies, enabling enhanced interpretation of disease-associated variants and genes 📌 The estimation of transcription factor activity solely from bulk or single-cell gene expression data to identify driver regulators from case-control studies. ➡ More details: https://lnkd.in/eiytSjrv #clemsonuniversity #spatialomics #spatialbiology #singlecellanalysis #singlecell

This method builds upon a structural graph describing regulatory causality between all genes and intends to construct a transcriptome-wide gene regulatory network (GRN), rather than local causal inference on a single exposure-outcome pair as traditional Mendelian randomization does. Providing a comprehensive map of gene interactions, transcriptome-wide GRNs can help us understand cellular mechanisms and disease pathways p/b Purdue University, UCBpharma, UC Irvine, Zhongli Jiang, Zhenyu Xu, Min Zhang, Dabao Zhang #transcriptomics #knowledgegraphs #multiomics https://lnkd.in/gEkHF2kb

Nature Genetics Article Supervised discovery of interpretable gene programs from single-cell data The authors show how Spectra, the cutting-edge algorithm, supports single-cell gene expression analysis while considering batch effects. 🚀 Say goodbye to technical artefacts and hello to actionable insights! 💡🔬 🌟 Key Features:  ✅ Unleashes novel gene programs  ✅ Incorporates existing gene sets  ✅ Enhances interpretability  ✅ Advances cell-type-specific insights ✅ Ideal for tumour immune contexts #Bioinformatics #DataScience #PrecisionMedicine #AI #singlecell  https://lnkd.in/erhyCv94

With new tools and alternatives to CRISPR making waves in gene editing science, it is clear that we are on the verge of a technological breakthrough when it comes to treating these new diseases. Accurate gene editing can treat all sorts of illnesses and leave a profound impact on the lives of patients. #GeneEditing #Healthcare #Innovation